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LNCC Training: Unable to learn (very unstable) #527
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JannikLa
changed the title
LNNC Training: Unable to learn (very unstable)
LNCC Training: Unable to learn (very unstable)
Jun 7, 2023
I haven't worked with the pytorch version that much especially recently, but just so I know -- when you say the MSE version worked, what were the hyperparameters that you used? What do you mean by this line -- what does 'overfit' mean here?
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Task (what are you trying to do/register?)
I am registering two T1 3D images from the OASIS data set (L2Reg challenge).
The scans are preprocessed (skull-stripped, aligned, normalized).
I am taking a fixed image from one subject and randomly select another subject as moving image (examples below).
I invested a lot if time in figuring out what is wrong. Maybe someone can give hints on what I could try or what might be wrong in my setup. Any help is appreciated!
What have you tried
I am using the pytroch implemention of voxelmorph. A dataloader loads the inputs to the network.
Details of experiments
self.flow.weight = nn.Parameter(Normal(0, 1e-5).sample(self.flow.weight.shape))
(networks.py, l 214)Image of training loss with maxed out smoothing in visualization ("baseline" setup from above)
Image of training loss (LNCC) when overfitting on a pair of images with large initialization weights (Normal(0, 10))
Image of input data
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